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Role of AI and digital pathology for colorectal immuno-oncology

Immunotherapy deals with therapeutic interventions to arrest the progression of tumours using the immune system. These include checkpoint inhibitors, T-cell manipulation, cytokines, oncolytic viruses and tumour vaccines. In this paper, we present a survey of the latest developments on immunotherapy...

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Autores principales: Bilal, Mohsin, Nimir, Mohammed, Snead, David, Taylor, Graham S., Rajpoot, Nasir
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9814831/
https://www.ncbi.nlm.nih.gov/pubmed/36183010
http://dx.doi.org/10.1038/s41416-022-01986-1
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author Bilal, Mohsin
Nimir, Mohammed
Snead, David
Taylor, Graham S.
Rajpoot, Nasir
author_facet Bilal, Mohsin
Nimir, Mohammed
Snead, David
Taylor, Graham S.
Rajpoot, Nasir
author_sort Bilal, Mohsin
collection PubMed
description Immunotherapy deals with therapeutic interventions to arrest the progression of tumours using the immune system. These include checkpoint inhibitors, T-cell manipulation, cytokines, oncolytic viruses and tumour vaccines. In this paper, we present a survey of the latest developments on immunotherapy in colorectal cancer (CRC) and the role of artificial intelligence (AI) in this context. Among these, microsatellite instability (MSI) is perhaps the most popular IO biomarker globally. We first discuss the MSI status of tumours, its implications for patient management, and its relationship to immune response. In recent years, several aspiring studies have used AI to predict the MSI status of patients from digital whole-slide images (WSIs) of routine diagnostic slides. We present a survey of AI literature on the prediction of MSI and tumour mutation burden from digitised WSIs of haematoxylin and eosin-stained diagnostic slides. We discuss AI approaches in detail and elaborate their contributions, limitations and key takeaways to drive future research. We further expand this survey to other IO-related biomarkers like immune cell infiltrates and alternate data modalities like immunohistochemistry and gene expression. Finally, we underline possible future directions in immunotherapy for CRC and promise of AI to accelerate this exploration for patient benefits.
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spelling pubmed-98148312023-01-06 Role of AI and digital pathology for colorectal immuno-oncology Bilal, Mohsin Nimir, Mohammed Snead, David Taylor, Graham S. Rajpoot, Nasir Br J Cancer Review Article Immunotherapy deals with therapeutic interventions to arrest the progression of tumours using the immune system. These include checkpoint inhibitors, T-cell manipulation, cytokines, oncolytic viruses and tumour vaccines. In this paper, we present a survey of the latest developments on immunotherapy in colorectal cancer (CRC) and the role of artificial intelligence (AI) in this context. Among these, microsatellite instability (MSI) is perhaps the most popular IO biomarker globally. We first discuss the MSI status of tumours, its implications for patient management, and its relationship to immune response. In recent years, several aspiring studies have used AI to predict the MSI status of patients from digital whole-slide images (WSIs) of routine diagnostic slides. We present a survey of AI literature on the prediction of MSI and tumour mutation burden from digitised WSIs of haematoxylin and eosin-stained diagnostic slides. We discuss AI approaches in detail and elaborate their contributions, limitations and key takeaways to drive future research. We further expand this survey to other IO-related biomarkers like immune cell infiltrates and alternate data modalities like immunohistochemistry and gene expression. Finally, we underline possible future directions in immunotherapy for CRC and promise of AI to accelerate this exploration for patient benefits. Nature Publishing Group UK 2022-10-01 2023-01-26 /pmc/articles/PMC9814831/ /pubmed/36183010 http://dx.doi.org/10.1038/s41416-022-01986-1 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Review Article
Bilal, Mohsin
Nimir, Mohammed
Snead, David
Taylor, Graham S.
Rajpoot, Nasir
Role of AI and digital pathology for colorectal immuno-oncology
title Role of AI and digital pathology for colorectal immuno-oncology
title_full Role of AI and digital pathology for colorectal immuno-oncology
title_fullStr Role of AI and digital pathology for colorectal immuno-oncology
title_full_unstemmed Role of AI and digital pathology for colorectal immuno-oncology
title_short Role of AI and digital pathology for colorectal immuno-oncology
title_sort role of ai and digital pathology for colorectal immuno-oncology
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9814831/
https://www.ncbi.nlm.nih.gov/pubmed/36183010
http://dx.doi.org/10.1038/s41416-022-01986-1
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